We are glad to present the proceedings of the 5th biennial conference in the Intelligent Data Analysis series. The conference took place in Berlin, Germany, August 28–30, 2003. IDA has by now clearly grown up. Started as a small si- symposium of a larger conference in 1995 in Baden-Baden (Germany) it quickly attractedmoreinterest(bothsubmission-andattendance-wise),andmovedfrom London (1997) to Amsterdam (1999), and two years ago to Lisbon. Submission ratesalongwiththeeverimprovingqualityofpapershaveenabledtheor- nizers to assemble increasingly consistent and high-quality programs. This year we were again overwhelmed by yet another record-breaking submission rate of 180 papers. At the Program Chairs meeting we were – based on roughly 500 reviews – in the lucky position of carefully selecting 17 papers for oral and 42 for poster presentation. Poster presenters were given the opportunity to summarize their papers in 3-minute spotlight presentations. The oral, spotlight and poster presentations were then scheduled in a single-track, 2. 5-day conference program, summarized in this book. In accordance with the goal of IDA, “to bring together researchers from diverse disciplines,” we achieved a nice balance of presentations from the more theoreticalside(bothstatisticsandcomputerscience)aswellasmoreapplicati- oriented areas that illustrate how these techniques can be used in practice. Work presented in these proceedings ranges from theoretical contributions dealing, for example, with data cleaning and compression all the way to papers addressing practical problems in the areas of text classi?cation and sales-rate predictions. A considerable number of papers also center around the currently so popular applications in bioinformatics.

One of the superb characteristics of Intelligent Data Analysis (IDA) is that it is an interdisciplinary ?eld in which researchers and practitioners from a number of areas are involved in a typical project. This also creates a challenge in which the success of a team depends on the participation of users and domain experts who need to interact with researchers and developers of any IDA system. All this is usually re?ected in successful projects and of course on the papers that were evaluated by this year’s program committee from which the ?nal program has been developed. In our call for papers, we solicited papers on (i) applications and tools, (ii) theory and general principles, and (iii) algorithms and techniques. We received a total of 184 papers, reviewing these was a major challenge. Each paper was assigned to three reviewers. In the end 46 papers were accepted, which are all included in the proceedings and presented at the conference. This year’s papers re?ect the results of applied and theoretical researchfrom a number of disciplines all of which are related to the ?eld of Intelligent Data Analysis. To have the best combination of theoretical and applied research and also provide the best focus, we have divided this year’s IDA program into tu- rials, invited talks, panel discussions and technical sessions.

This book constitutes the refereed proceedings of the Third International Symposium on Intelligent Data Analysis, IDA-99 held in Amsterdam, The Netherlands in August 1999. The 21 revised full papers and 23 posters presented in the book were carefully reviewed and selected from a total of more than 100 submissions. The papers address all current aspects of intelligent data analysis; they are organized in sections on learning, visualization, classification and clustering, integration, applications and media mining.

This book constitutes the Proceeding of the Sixth International Conference on Intelligent Data Analysis and Applications, October 15–18, 2019, Arad, Romania. This edition is technically co-sponsored by “Aurel Vlaicu” University of Arad, Romania, Southwest Jiaotong University, Fujian University of Technology, Chang’an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology), China, Romanian Academy, and General Association of Engineers in Romania - Arad Section. The book covers a range of topics: Machine Learning, Intelligent Control, Pattern Recognition, Computational Intelligence, Signal Analysis, Modeling and Visualization, Multimedia Sensing and Sensory Systems, Signal control, Imaging and Processing, Information System Security, Cryptography and Cryptanalysis, Databases and Data Mining, Information Hiding, Cloud Computing, Information Retrieval and Integration, Robotics, Control, Agents, Command, Control, Communication and Computers (C4), Swarming Technology, Sensor Technology, Smart cities. The book offers a timely, board snapshot of new development including trends and challenges that are yielding recent research directions in different areas of intelligent data analysis and applications. The book provides useful information to professors, researchers, and graduated students in area of intelligent data analysis and applications.

This book constitutes the proceedings of the 21st International Symposium on Intelligent Data Analysis, IDA 2022, which was held in Louvain-la-Neuve, Belgium, during April 12-14, 2023. The 38 papers included in this book were carefully reviewed and selected from 91 submissions. IDA is an international symposium presenting advances in the intelligent analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale.

This book constitutes the refereed proceedings of the 10th International Conference on Intelligent Data Analysis, IDA 2011, held in Porto, Portugal, in October 2011. The 19 revised full papers and 16 revised poster papers resented together with 3 invited papers were carefully reviewed and selected from 73 submissions. All current aspects of intelligent data analysis are addressed, particularly intelligent support for modeling and analyzing complex, dynamical systems. The papers offer intelligent support for understanding evolving scientific and social systems including data collection and acquisition, such as crowd sourcing; data cleaning, semantics and markup; searching for data and assembling datasets from multiple sources; data processing, including workflows, mixed-initiative data analysis, and planning; data and information fusion; incremental, mixed-initiative model development, testing and revision; and visualization and dissemination of results; etc.

This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

This book constitutes the refereed proceedings of the Second International Symposium on Intelligent Data Analysis, IDA-97, held in London, UK, in August 1997. The volume presents 50 revised full papers selected from a total of 107 submissions. Also included is a keynote, Intelligent Data Analysis: Issues and Opportunities, by David J. Hand. The papers are organized in sections on exploratory data analysis, preprocessing and tools; classification and feature selection; medical applications; soft computing; knowledge discovery and data mining; estimation and clustering; data quality; qualitative models.

This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Data Analysis, IDA 2009, held in Lyon, France, August 31 - September 2, 2009. The 33 revised papers, 18 full oral presentations and 15 poster and short oral presentations, presented were carefully reviewed and selected from almost 80 submissions. All current aspects of this interdisciplinary field are addressed; for example interactive tools to guide and support data analysis in complex scenarios, increasing availability of automatically collected data, tools that intelligently support and assist human analysts, how to control clustering results and isotonic classification trees. In general the areas covered include statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.